Ontology highlight
ABSTRACT: Background
Adolescence is marked by a sharp increase in the incidence of depression, especially in females. Identification of risk for depressive disorders (DD) in this key developmental stage can help prevention efforts, mitigating the clinical and public burden of DD. While frequently used in diagnosis, nonverbal behaviors are relatively understudied as risk markers for DD. Digital technology, such as facial recognition, may provide objective, fast, efficient, and cost-effective means of measuring nonverbal behavior.Method
Here, we analyzed video-recorded clinical interviews of 359 never-depressed adolescents females via commercially available facial emotion recognition software.Results
We found that average head and facial movements forecast future first onset of
SUBMITTER: Ozturk S
PROVIDER: S-EPMC11496224 | biostudies-literature | 2024 Oct
REPOSITORIES: biostudies-literature